An object-oriented framework to enable workflow evolution across materials acceleration platforms
Progress in data-driven self-driving laboratories for solving materials grand challenges has accelerated with the advent of machine learning, robotics, and automation, but they are usually designed with specific materials and processes in mind. To develop the next generation of materials acceleratio...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Online Access: | https://hdl.handle.net/10356/164443 |
| _version_ | 1811694959724593152 |
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| author | Leong, Chang Jie Low, Andre Kai Yuan Recatala-Gomez, Jose Velasco, Pablo Quijano Vissol-Gaudin, Eleonore Tan, Jin Da Ramalingam, Balamurugan Made, Riko I Pethe, Shreyas Dinesh Sebastian, Saumya Lim, Yee-Fun Khoo, Jonathan Zi Hui Bai, Yang Cheng, Jayce Jian Wei Hippalgaonkar, Kedar |
| author2 | School of Materials Science and Engineering |
| author_facet | School of Materials Science and Engineering Leong, Chang Jie Low, Andre Kai Yuan Recatala-Gomez, Jose Velasco, Pablo Quijano Vissol-Gaudin, Eleonore Tan, Jin Da Ramalingam, Balamurugan Made, Riko I Pethe, Shreyas Dinesh Sebastian, Saumya Lim, Yee-Fun Khoo, Jonathan Zi Hui Bai, Yang Cheng, Jayce Jian Wei Hippalgaonkar, Kedar |
| author_sort | Leong, Chang Jie |
| collection | NTU |
| description | Progress in data-driven self-driving laboratories for solving materials grand challenges has accelerated with the advent of machine learning, robotics, and automation, but they are usually designed with specific materials and processes in mind. To develop the next generation of materials acceleration platforms (MAPs), we propose a unified framework to enable collaboration between MAPs, leveraging on object-oriented programming principles using research groups around theworldthatwouldbeabletoeffectively evolveexperimentalworkflows.Wedemonstratetheframeworkvia three experimental case studies from disparate fields to illustrate theevolutionof,andseamlessintegrationbetween,workflows,promoting efficient resource utilization and collaboration. Moving forward, we project our framework on three other research areas that would benefit from such an evolving workflow. Through the wide adoption of our framework, we envision a collaborative, connected, global community of MAPs working together to solve scientific grand challenges. |
| first_indexed | 2024-10-01T07:15:52Z |
| format | Journal Article |
| id | ntu-10356/164443 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:15:52Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1644432023-07-14T16:07:28Z An object-oriented framework to enable workflow evolution across materials acceleration platforms Leong, Chang Jie Low, Andre Kai Yuan Recatala-Gomez, Jose Velasco, Pablo Quijano Vissol-Gaudin, Eleonore Tan, Jin Da Ramalingam, Balamurugan Made, Riko I Pethe, Shreyas Dinesh Sebastian, Saumya Lim, Yee-Fun Khoo, Jonathan Zi Hui Bai, Yang Cheng, Jayce Jian Wei Hippalgaonkar, Kedar School of Materials Science and Engineering Institute of Materials Research and Engineering, A*STAR Engineering::Materials MAP6: Development Data Driven Progress in data-driven self-driving laboratories for solving materials grand challenges has accelerated with the advent of machine learning, robotics, and automation, but they are usually designed with specific materials and processes in mind. To develop the next generation of materials acceleration platforms (MAPs), we propose a unified framework to enable collaboration between MAPs, leveraging on object-oriented programming principles using research groups around theworldthatwouldbeabletoeffectively evolveexperimentalworkflows.Wedemonstratetheframeworkvia three experimental case studies from disparate fields to illustrate theevolutionof,andseamlessintegrationbetween,workflows,promoting efficient resource utilization and collaboration. Moving forward, we project our framework on three other research areas that would benefit from such an evolving workflow. Through the wide adoption of our framework, we envision a collaborative, connected, global community of MAPs working together to solve scientific grand challenges. Agency for Science, Technology and Research (A*STAR) National Research Foundation (NRF) Submitted/Accepted version We acknowledge funding from Accelerated Materials Development for Manufacturing Program A1898b0043 at A*STAR via the AME Programmatic Fund by the Agency for Science, Technology and Research. K.H. also acknowledges funding from the NRF Fellowship NRF-NRFF13-2021- 0011. 2023-01-25T08:00:10Z 2023-01-25T08:00:10Z 2022 Journal Article Leong, C. J., Low, A. K. Y., Recatala-Gomez, J., Velasco, P. Q., Vissol-Gaudin, E., Tan, J. D., Ramalingam, B., Made, R. I., Pethe, S. D., Sebastian, S., Lim, Y., Khoo, J. Z. H., Bai, Y., Cheng, J. J. W. & Hippalgaonkar, K. (2022). An object-oriented framework to enable workflow evolution across materials acceleration platforms. Matter, 5(10), 3124-3134. https://dx.doi.org/10.1016/j.matt.2022.08.017 2590-2385 https://hdl.handle.net/10356/164443 10.1016/j.matt.2022.08.017 10 5 3124 3134 en A1898b0043 NRF-NRFF13-2021-0011 Matter © 2022 Elsevier Inc. All rights reserved. This paper was published in Matter and is made available with permission of Elsevier Inc. application/pdf |
| spellingShingle | Engineering::Materials MAP6: Development Data Driven Leong, Chang Jie Low, Andre Kai Yuan Recatala-Gomez, Jose Velasco, Pablo Quijano Vissol-Gaudin, Eleonore Tan, Jin Da Ramalingam, Balamurugan Made, Riko I Pethe, Shreyas Dinesh Sebastian, Saumya Lim, Yee-Fun Khoo, Jonathan Zi Hui Bai, Yang Cheng, Jayce Jian Wei Hippalgaonkar, Kedar An object-oriented framework to enable workflow evolution across materials acceleration platforms |
| title | An object-oriented framework to enable workflow evolution across materials acceleration platforms |
| title_full | An object-oriented framework to enable workflow evolution across materials acceleration platforms |
| title_fullStr | An object-oriented framework to enable workflow evolution across materials acceleration platforms |
| title_full_unstemmed | An object-oriented framework to enable workflow evolution across materials acceleration platforms |
| title_short | An object-oriented framework to enable workflow evolution across materials acceleration platforms |
| title_sort | object oriented framework to enable workflow evolution across materials acceleration platforms |
| topic | Engineering::Materials MAP6: Development Data Driven |
| url | https://hdl.handle.net/10356/164443 |
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